Mould Characterization and Mycotoxin Quantification of Chia Seeds (Salvia hispanica L.) Grown in Kenya
Bibliographic record
Abstract
Chia seeds are functional food that have been considered highly nutritious. They have high levels of polyunsaturated fatty acid content therefore counteract lifestyle disorder such as cardiovascular diseases. This study sought to determine the level of mould contamination in chia seeds; enumeration and characterization of the types of molds and quantification of mycotoxin level, for chia seeds grown and sold in Kenya. A complete randomized block design with triplicates was used in the study. Samples were collected at random from farmers and distributors in Nyeri, Nakuru, Busia and Trans Nzoia counties. Moulds species were isolated from PDA and MEA Medias and morphological characteristics was determined under X 40 magnification power. Mould counts were found to be between 1.33 X 103cfu/ml to 2.67 X 103cfu/ml. Mould characterization done by microscopic and macroscopic technique showed evidence of Rhizopus spp, Trichoderma spp and Fusarium spp. Amongst the three genera found, Rhizopus spp was the predominantly occurring mould. The percentage moisture content of chia seeds samples ranged from 6.49±1.26 and 9.16±0.43. Significant variations on moisture content (p< 0.05) were observed among chia samples from different farmers. Aflatoxin was not detected in all chia samples. It can therefore be concluded that the chia samples were not contaminated with aflatoxin although different species of mold were present. Farmers need to be trained on proper postharvest handling methods of chia seeds, as well as proper storage and an objective method of analyzing the moisture content of the chia seeds need to be developed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".